1
|
Meisenzahl C, Gillette K, Prassl AJ, Plank G, Sapp JL, Wang L. BOATMAP: Bayesian Optimization Active Targeting for Monomorphic Arrhythmia Pace-mapping. Comput Biol Med 2024; 182:109201. [PMID: 39342676 DOI: 10.1016/j.compbiomed.2024.109201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 09/02/2024] [Accepted: 09/22/2024] [Indexed: 10/01/2024]
Abstract
Recent advances in machine learning and deep learning have presented new opportunities for learning to localize the origin of ventricular activation from 12-lead electrocardiograms (ECGs), an important step in guiding ablation therapies for ventricular tachycardia. Passively learning from population data is faced with challenges due to significant variations among subjects, and building a patient-specific model raises the open question of where to select pace-mapping data for training. This work introduces BOATMAP, a novel active learning approach designed to provide clinicians with interpretable guidance that progressively assists in locating the origin of ventricular activation from 12-lead ECGs. BOATMAP inverts the input-output relationship in traditional machine learning solutions to this problem and learns the similarity between a target ECG and a paced ECG as a function of the pacing site coordinates. Using Gaussian processes (GP) as a surrogate model, BOATMAP iteratively refines the estimated similarity landscape while providing suggestions to clinicians regarding the next optimal pacing site. Furthermore, it can incorporate constraints to avoid suggesting pacing in non-viable regions such as the core of the myocardial scar. Tested in a realistic simulation environment in various heart geometries and tissue properties, BOATMAP demonstrated the ability to accurately localize the origin of activation, achieving an average localization accuracy of 3.9±3.6mm with only 8.0±4.0 pacing sites. BOATMAP offers real-time interpretable guidance for accurate localization and enhancing clinical decision-making.
Collapse
Affiliation(s)
| | - Karli Gillette
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria.
| | - Anton J Prassl
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
| | - Gernot Plank
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria.
| | - John L Sapp
- QEII Health Sciences Centre, Dalhousie University, Halifax, Nova Scotia, Canada.
| | - Linwei Wang
- Rochester Institute of Technology, Rochester, NY, USA.
| |
Collapse
|
2
|
Jiang X, Missel R, Toloubidokhti M, Gillette K, Prassl AJ, Plank G, Horacek BM, Sapp JL, Wang L. Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2733-2744. [PMID: 38478452 PMCID: PMC11330696 DOI: 10.1109/tmi.2024.3377094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
State-space modeling (SSM) provides a general framework for many image reconstruction tasks. Error in a priori physiological knowledge of the imaging physics, can bring incorrectness to solutions. Modern deep-learning approaches show great promise but lack interpretability and rely on large amounts of labeled data. In this paper, we present a novel hybrid SSM framework for electrocardiographic imaging (ECGI) to leverage the advantage of state-space formulations in data-driven learning. We first leverage the physics-based forward operator to supervise the learning. We then introduce neural modeling of the transition function and the associated Bayesian filtering strategy. We applied the hybrid SSM framework to reconstruct electrical activity on the heart surface from body-surface potentials. In unsupervised settings of both in-silico and in-vivo data without cardiac electrical activity as the ground truth to supervise the learning, we demonstrated improved ECGI performances of the hybrid SSM framework trained from a small number of ECG observations in comparison to the fixed SSM. We further demonstrated that, when in-silico simulation data becomes available, mixed supervised and unsupervised training of the hybrid SSM achieved a further 40.6% and 45.6% improvements, respectively, in comparison to traditional ECGI baselines and supervised data-driven ECGI baselines for localizing the origin of ventricular activations in real data.
Collapse
|
3
|
Wülfers EM, Moss R, Lehrmann H, Arentz T, Westermann D, Seemann G, Odening KE, Steinfurt J. Whole-heart computational modelling provides further mechanistic insights into ST-elevation in Brugada syndrome. INTERNATIONAL JOURNAL OF CARDIOLOGY. HEART & VASCULATURE 2024; 51:101373. [PMID: 38464963 PMCID: PMC10924145 DOI: 10.1016/j.ijcha.2024.101373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/08/2024] [Accepted: 02/21/2024] [Indexed: 03/12/2024]
Abstract
Background Brugada syndrome (BrS) is characterized by dynamic ST-elevations in right precordial leads and increased risk of ventricular fibrillation and sudden cardiac death. As the mechanism underlying ST-elevation and malignant arrhythmias is controversial computational modeling can aid in exploring the disease mechanism. Thus we aim to test the main competing hypotheses ('delayed depolarization' vs. 'early repolarization') of BrS in a whole-heart computational model. Methods In a 3D whole-heart computational model, delayed epicardial RVOT activation with local conduction delay was simulated by reducing conductivity in the epicardial RVOT. Early repolarization was simulated by instead increasing the transient outward potassium current (Ito) in the same region. Additionally, a reduction in the fast sodium current (INa) was incorporated in both models. Results Delayed depolarization with local conduction delay in the computational model resulted in coved-type ST-elevation with negative T-waves in the precordial surface ECG leads. 'Saddleback'-shaped ST-elevation was obtained with reduced substrate extent or thickness. Increased Ito simulations showed early repolarization in the RVOT with a descending but not coved-type ST-elevation. Reduced INa did not show a significant effect on ECG morphology. Conclusions In this whole-heart BrS computational model of both major hypotheses, realistic coved-type ECG resulted only from delayed epicardial RVOT depolarization with local conduction delay but not early repolarizing ion channel modifications. These simulations provide further support for the depolarization hypothesis as electrophysiological mechanism underlying BrS.
Collapse
Affiliation(s)
- Eike M Wülfers
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Physics and Astronomy, Faculty of Sciences, Ghent University, Ghent, Belgium
| | - Robin Moss
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Heiko Lehrmann
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Arentz
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dirk Westermann
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katja E Odening
- Translational Cardiology, Department of Cardiology and Institute of Physiology, University Hospital Bern, University of Bern, Switzerland
| | - Johannes Steinfurt
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|
4
|
Gillette K, Gsell MAF, Nagel C, Bender J, Winkler B, Williams SE, Bär M, Schäffter T, Dössel O, Plank G, Loewe A. MedalCare-XL: 16,900 healthy and pathological synthetic 12 lead ECGs from electrophysiological simulations. Sci Data 2023; 10:531. [PMID: 37553349 PMCID: PMC10409805 DOI: 10.1038/s41597-023-02416-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/25/2023] [Indexed: 08/10/2023] Open
Abstract
Mechanistic cardiac electrophysiology models allow for personalized simulations of the electrical activity in the heart and the ensuing electrocardiogram (ECG) on the body surface. As such, synthetic signals possess known ground truth labels of the underlying disease and can be employed for validation of machine learning ECG analysis tools in addition to clinical signals. Recently, synthetic ECGs were used to enrich sparse clinical data or even replace them completely during training leading to improved performance on real-world clinical test data. We thus generated a novel synthetic database comprising a total of 16,900 12 lead ECGs based on electrophysiological simulations equally distributed into healthy control and 7 pathology classes. The pathological case of myocardial infraction had 6 sub-classes. A comparison of extracted features between the virtual cohort and a publicly available clinical ECG database demonstrated that the synthetic signals represent clinical ECGs for healthy and pathological subpopulations with high fidelity. The ECG database is split into training, validation, and test folds for development and objective assessment of novel machine learning algorithms.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - Claudia Nagel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Jule Bender
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Benjamin Winkler
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
| | - Steven E Williams
- King's College London, London, United Kingdom
- University of Edinburgh, Edinburgh, United Kingdom
| | - Markus Bär
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
| | - Tobias Schäffter
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
- King's College London, London, United Kingdom
- Biomedical Engineering, Technische Universität Berlin, Einstein Centre Digital Future, Berlin, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| |
Collapse
|
5
|
Dogrusoz YS, Rasoolzadeh N, Ondrusova B, Hlivak P, Zelinka J, Tysler M, Svehlikova J. Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data. Front Physiol 2023; 14:1197778. [PMID: 37362428 PMCID: PMC10288213 DOI: 10.3389/fphys.2023.1197778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).
Collapse
Affiliation(s)
- Yesim Serinagaoglu Dogrusoz
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Nika Rasoolzadeh
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Beata Ondrusova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
- Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Bratislava, Slovakia
| | - Peter Hlivak
- National Institute for Cardiovascular Diseases, Bratislava, Slovakia
| | - Jan Zelinka
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Milan Tysler
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Jana Svehlikova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| |
Collapse
|
6
|
Ferrero JM, Gonzalez-Ascaso A, Matas JFR. The mechanisms of potassium loss in acute myocardial ischemia: New insights from computational simulations. Front Physiol 2023; 14:1074160. [PMID: 36923288 PMCID: PMC10009276 DOI: 10.3389/fphys.2023.1074160] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/13/2023] [Indexed: 03/03/2023] Open
Abstract
Acute myocardial ischemia induces hyperkalemia (accumulation of extracellular potassium), a major perpetrator of lethal reentrant ventricular arrhythmias. Despite considerable experimental efforts to explain this pathology in the last decades, the intimate mechanisms behind hyperkalemia remain partially unknown. In order to investigate these mechanisms, we developed a novel computational model of acute myocardial ischemia which couples a) an electrophysiologically detailed human cardiomyocyte model that incorporates modifications to account for ischemia-induced changes in transmembrane currents, with b) a model of cardiac tissue and extracellular K + transport. The resulting model is able to reproduce and explain the triphasic time course of extracellular K + concentration within the ischemic zone, with values of [ K + ] o close to 14 mmol/L in the central ischemic zone after 30 min. In addition, the formation of a [ K + ] o border zone of approximately 1.2 cm 15 min after the onset of ischemia is predicted by the model. Our results indicate that the primary rising phase of [ K + ] o is mainly due to the imbalance between K + efflux, that increases slightly, and K + influx, that follows a reduction of the NaK pump activity by more than 50%. The onset of the plateau phase is caused by the appearance of electrical alternans (a novel mechanism identified by the model), which cause an abrupt reduction in the K + efflux. After the plateau, the secondary rising phase of [ K + ] o is caused by a subsequent imbalance between the K + influx, which continues to decrease slowly, and the K + efflux, which remains almost constant. Further, the study shows that the modulation of these mechanisms by the electrotonic coupling is the main responsible for the formation of the ischemic border zone in tissue, with K + transport playing only a minor role. Finally, the results of the model indicate that the injury current established between the healthy and the altered tissue is not sufficient to depolarize non-ischemic cells within the healthy tissue.
Collapse
Affiliation(s)
- Jose M Ferrero
- Centro de Investigacion e Innovacion en Bioingenieria, Universitat Politecnica de Valencia, Valencia, Spain
| | - Ana Gonzalez-Ascaso
- Centro de Investigacion e Innovacion en Bioingenieria, Universitat Politecnica de Valencia, Valencia, Spain.,Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Jose F Rodriguez Matas
- Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| |
Collapse
|
7
|
Gillette K, Gsell MAF, Strocchi M, Grandits T, Neic A, Manninger M, Scherr D, Roney CH, Prassl AJ, Augustin CM, Vigmond EJ, Plank G. A personalized real-time virtual model of whole heart electrophysiology. Front Physiol 2022; 13:907190. [PMID: 36213235 PMCID: PMC9539798 DOI: 10.3389/fphys.2022.907190] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/15/2022] [Indexed: 01/12/2023] Open
Abstract
Computer models capable of representing the intrinsic personal electrophysiology (EP) of the heart in silico are termed virtual heart technologies. When anatomy and EP are tailored to individual patients within the model, such technologies are promising clinical and industrial tools. Regardless of their vast potential, few virtual technologies simulating the entire organ-scale EP of all four-chambers of the heart have been reported and widespread clinical use is limited due to high computational costs and difficulty in validation. We thus report on the development of a novel virtual technology representing the electrophysiology of all four-chambers of the heart aiming to overcome these limitations. In our previous work, a model of ventricular EP embedded in a torso was constructed from clinical magnetic resonance image (MRI) data and personalized according to the measured 12 lead electrocardiogram (ECG) of a single subject under normal sinus rhythm. This model is then expanded upon to include whole heart EP and a detailed representation of the His-Purkinje system (HPS). To test the capacities of the personalized virtual heart technology to replicate standard clinical morphological ECG features under such conditions, bundle branch blocks within both the right and the left ventricles under two different conduction velocity settings are modeled alongside sinus rhythm. To ensure clinical viability, model generation was completely automated and simulations were performed using an efficient real-time cardiac EP simulator. Close correspondence between the measured and simulated 12 lead ECG was observed under normal sinus conditions and all simulated bundle branch blocks manifested relevant clinical morphological features.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Thomas Grandits
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Martin Manninger
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Daniel Scherr
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | | | - Anton J. Prassl
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | | | - Gernot Plank
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- *Correspondence: Gernot Plank,
| |
Collapse
|
8
|
Moss R, Wülfers EM, Lewetag R, Hornyik T, Perez-Feliz S, Strohbach T, Menza M, Krafft A, Odening KE, Seemann G. A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution. PLoS One 2022; 17:e0270559. [PMID: 35771854 PMCID: PMC9246225 DOI: 10.1371/journal.pone.0270559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 06/13/2022] [Indexed: 11/19/2022] Open
Abstract
Computational modeling of electrophysiological properties of the rabbit heart is a commonly used way to enhance and/or complement findings from classic lab work on single cell or tissue levels. Yet, thus far, there was no possibility to extend the scope to include the resulting body surface potentials as a way of validation or to investigate the effect of certain pathologies. Based on CT imaging, we developed the first openly available computational geometrical model not only of the whole heart but also the complete torso of the rabbit. Additionally, we fabricated a 32-lead ECG-vest to record body surface potential signals of the aforementioned rabbit. Based on the developed geometrical model and the measured signals, we then optimized the activation sequence of the ventricles, recreating the functionality of the Purkinje network, and we investigated different apico-basal and transmural gradients in action potential duration. Optimization of the activation sequence resulted in an average root mean square error between measured and simulated signal of 0.074 mV/ms for all leads. The best-fit T-Wave, compared to measured data (0.038 mV/ms), resulted from incorporating an action potential duration gradient from base to apex with a respective shortening of 20 ms and a transmural gradient with a shortening of 15 ms from endocardium to epicardium. By making our model and measured data openly available, we hope to give other researchers the opportunity to verify their research, as well as to create the possibility to investigate the impact of electrophysiological alterations on body surface signals for translational research.
Collapse
Affiliation(s)
- Robin Moss
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- * E-mail:
| | - Eike M. Wülfers
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Raphaela Lewetag
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
| | - Tibor Hornyik
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Translational Cardiology, Department of Cardiology and Department of Physiology, University Hospital Bern, Bern, Switzerland
| | - Stefanie Perez-Feliz
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
| | - Tim Strohbach
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Marius Menza
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Axel Krafft
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Katja E. Odening
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
- Translational Cardiology, Department of Cardiology and Department of Physiology, University Hospital Bern, Bern, Switzerland
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|
9
|
Ling Y, Pang W, Liu J, Page M, Xu Y, Zhao G, Stalla D, Xie J, Zhang Y, Yan Z. Bioinspired elastomer composites with programmed mechanical and electrical anisotropies. Nat Commun 2022; 13:524. [PMID: 35082331 PMCID: PMC8791960 DOI: 10.1038/s41467-022-28185-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 01/04/2022] [Indexed: 12/26/2022] Open
Abstract
Concepts that draw inspiration from soft biological tissues have enabled significant advances in creating artificial materials for a range of applications, such as dry adhesives, tissue engineering, biointegrated electronics, artificial muscles, and soft robots. Many biological tissues, represented by muscles, exhibit directionally dependent mechanical and electrical properties. However, equipping synthetic materials with tissue-like mechanical and electrical anisotropies remains challenging. Here, we present the bioinspired concepts, design principles, numerical modeling, and experimental demonstrations of soft elastomer composites with programmed mechanical and electrical anisotropies, as well as their integrations with active functionalities. Mechanically assembled, 3D structures of polyimide serve as skeletons to offer anisotropic, nonlinear mechanical properties, and crumpled conductive surfaces provide anisotropic electrical properties, which can be used to construct bioelectronic devices. Finite element analyses quantitatively capture the key aspects that govern mechanical anisotropies of elastomer composites, providing a powerful design tool. Incorporation of 3D skeletons of thermally responsive polycaprolactone into elastomer composites allows development of an active artificial material that can mimic adaptive mechanical behaviors of skeleton muscles at relaxation and contraction states. Furthermore, the fabrication process of anisotropic elastomer composites is compatible with dielectric elastomer actuators, indicating potential applications in humanoid artificial muscles and soft robots.
Collapse
Affiliation(s)
- Yun Ling
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Wenbo Pang
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084, Beijing, China.,Center for Flexible Electronics Technology, Tsinghua University, 100084, Beijing, China
| | - Jianxing Liu
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084, Beijing, China.,Center for Flexible Electronics Technology, Tsinghua University, 100084, Beijing, China
| | - Margaret Page
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Yadong Xu
- Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Ganggang Zhao
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - David Stalla
- Electron Microscopy Core, University of Missouri, Columbia, MO, 65211, USA
| | - Jingwei Xie
- Department of Surgery-Transplant and Mary and Dick Holland Regenerative Medicine Program, College of Medicine, University of Nebraska Medical Center, Omaha, NE, 68130, USA
| | - Yihui Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084, Beijing, China. .,Center for Flexible Electronics Technology, Tsinghua University, 100084, Beijing, China.
| | - Zheng Yan
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA. .,Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, 65211, USA.
| |
Collapse
|
10
|
Moss R, Wülfers EM, Schuler S, Loewe A, Seemann G. A Fully-Coupled Electro-Mechanical Whole-Heart Computational Model: Influence of Cardiac Contraction on the ECG. Front Physiol 2022; 12:778872. [PMID: 34975532 PMCID: PMC8716847 DOI: 10.3389/fphys.2021.778872] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/17/2021] [Indexed: 01/12/2023] Open
Abstract
The ECG is one of the most commonly used non-invasive tools to gain insights into the electrical functioning of the heart. It has been crucial as a foundation in the creation and validation of in silico models describing the underlying electrophysiological processes. However, so far, the contraction of the heart and its influences on the ECG have mainly been overlooked in in silico models. As the heart contracts and moves, so do the electrical sources within the heart responsible for the signal on the body surface, thus potentially altering the ECG. To illuminate these aspects, we developed a human 4-chamber electro-mechanically coupled whole heart in silico model and embedded it within a torso model. Our model faithfully reproduces measured 12-lead ECG traces, circulatory characteristics, as well as physiological ventricular rotation and atrioventricular valve plane displacement. We compare our dynamic model to three non-deforming ones in terms of standard clinically used ECG leads (Einthoven and Wilson) and body surface potential maps (BSPM). The non-deforming models consider the heart at its ventricular end-diastatic, end-diastolic and end-systolic states. The standard leads show negligible differences during P-Wave and QRS-Complex, yet during T-Wave the leads closest to the heart show prominent differences in amplitude. When looking at the BSPM, there are no notable differences during the P-Wave, but effects of cardiac motion can be observed already during the QRS-Complex, increasing further during the T-Wave. We conclude that for the modeling of activation (P-Wave/QRS-Complex), the associated effort of simulating a complete electro-mechanical approach is not worth the computational cost. But when looking at ventricular repolarization (T-Wave) in standard leads as well as BSPM, there are areas where the signal can be influenced by cardiac motion of the heart to an extent that should not be ignored.
Collapse
Affiliation(s)
- Robin Moss
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, Medical Center-University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Eike Moritz Wülfers
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, Medical Center-University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, Medical Center-University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|
11
|
Gillette K, Gsell MAF, Bouyssier J, Prassl AJ, Neic A, Vigmond EJ, Plank G. Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology. Ann Biomed Eng 2021; 49:3143-3153. [PMID: 34431016 PMCID: PMC8671274 DOI: 10.1007/s10439-021-02825-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/26/2021] [Indexed: 11/28/2022]
Abstract
Personalized models of cardiac electrophysiology (EP) that match clinical observation with high fidelity, referred to as cardiac digital twins (CDTs), show promise as a tool for tailoring cardiac precision therapies. Building CDTs of cardiac EP relies on the ability of models to replicate the ventricular activation sequence under a broad range of conditions. Of pivotal importance is the His-Purkinje system (HPS) within the ventricles. Workflows for the generation and incorporation of HPS models are needed for use in cardiac digital twinning pipelines that aim to minimize the misfit between model predictions and clinical data such as the 12 lead electrocardiogram (ECG). We thus develop an automated two stage approach for HPS personalization. A fascicular-based model is first introduced that modulates the endocardial Purkinje network. Only emergent features of sites of earliest activation within the ventricular myocardium and a fast-conducting sub-endocardial layer are accounted for. It is then replaced by a topologically realistic Purkinje-based representation of the HPS. Feasibility of the approach is demonstrated. Equivalence between both HPS model representations is investigated by comparing activation patterns and 12 lead ECGs under both sinus rhythm and right-ventricular apical pacing. Predominant ECG morphology is preserved by both HPS models under sinus conditions, but elucidates differences during pacing.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
| | - Julien Bouyssier
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Anton J Prassl
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
| | | | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
| |
Collapse
|
12
|
Analysis of vulnerability to reentry in acute myocardial ischemia using a realistic human heart model. Comput Biol Med 2021; 141:105038. [PMID: 34836624 DOI: 10.1016/j.compbiomed.2021.105038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/25/2021] [Accepted: 11/12/2021] [Indexed: 11/21/2022]
Abstract
Electrophysiological alterations of the myocardium caused by acute ischemia constitute a pro-arrhythmic substrate for the generation of potentially lethal arrhythmias. Experimental evidence has shown that the main components of acute ischemia that induce these electrophysiological alterations are hyperkalemia, hypoxia (or anoxia in complete artery occlusion), and acidosis. However, the influence of each ischemic component on the likelihood of reentry is not completely established. Moreover, the role of the His-Purkinje system (HPS) in the initiation and maintenance of arrhythmias is not completely understood. In the present work, we investigate how the three components of ischemia affect the vulnerable window (VW) for reentry using computational simulations. In addition, we analyze the role of the HPS on arrhythmogenesis. A 3D biventricular/torso human model that includes a realistic geometry of the central and border ischemic zones with one of the most electrophysiologically detailed model of ischemia to date, as well as a realistic cardiac conduction system, were used to assess the VW for reentry. Four scenarios of ischemic severity corresponding to different minutes after coronary artery occlusion were simulated. Our results suggest that ischemic severity plays an important role in the generation of reentries. Indeed, this is the first 3D simulation study to show that ventricular arrhythmias could be generated under moderate ischemic conditions, but not in mild and severe ischemia. Moreover, our results show that anoxia is the ischemic component with the most significant effect on the width of the VW. Thus, a change in the level of anoxia from moderate to severe leads to a greater increment in the VW (40 ms), in comparison with the increment of 20 ms and 35 ms produced by the individual change in the level of hyperkalemia and acidosis, respectively. Finally, the HPS was a necessary element for the generation of approximately 17% of reentries obtained. The retrograde conduction from the myocardium to HPS in the ischemic region, conduction blocks in discrete sections of the HPS, and the degree of ischemia affecting Purkinje cells, are suggested as mechanisms that favor the generation of ventricular arrhythmias.
Collapse
|
13
|
Johnston BM, Johnston PR. Which bidomain conductivity is the most important for modelling heart and torso surface potentials during ischaemia? Comput Biol Med 2021; 137:104830. [PMID: 34534792 DOI: 10.1016/j.compbiomed.2021.104830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 08/29/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022]
Abstract
Mathematical simulations using the bidomain model, which represents cardiac tissue as consisting of an intracellular and an extracellular space, are a key approach that can be used to improve understanding of heart conditions such as ischaemia. However, key inputs to these models, such as the bidomain conductivity values, are not known with any certainty. Since efforts are underway to measure these values, it would be useful to be able to quantify the effect on model outputs of uncertainty in these inputs, and also to determine, if possible, which are the most important values to focus on in experimental studies. Our previous work has systematically studied the sensitivity of heart surface potentials to the bidomain conductivity values, and this was performed using a half-ellipsoidal model of the left ventricle. This study uses a bi-ventricular heart in a torso model and this time looks at the sensitivity of the torso surface potentials, as well as the heart surface potentials, to various conductivity values (blood, torso and the six bidomain conductivities). We found that both epicardial and torso potentials are the most sensitive to the intracellular longitudinal (along the cardiac fibres) conductivity (gil) with more minor sensitivity to the torso conductivity, and that changes in gil have a significant effect on the surface potential distributions on both the torso and the heart.
Collapse
Affiliation(s)
- Barbara M Johnston
- School of Environment and Science, Griffith University, Nathan, Queensland, 4111, Australia.
| | - Peter R Johnston
- School of Environment and Science, Griffith University, Nathan, Queensland, 4111, Australia
| |
Collapse
|
14
|
Riccio J, Alcaine A, Rocher S, Martinez-Mateu L, Laranjo S, Saiz J, Laguna P, Martínez JP. Characterization of Atrial Propagation Patterns and Fibrotic Substrate With a Modified Omnipolar Electrogram Strategy in Multi-Electrode Arrays. Front Physiol 2021; 12:674223. [PMID: 34539424 PMCID: PMC8446360 DOI: 10.3389/fphys.2021.674223] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 07/13/2021] [Indexed: 11/15/2022] Open
Abstract
Introduction: The omnipolar electrogram method was recently proposed to try to generate orientation-independent electrograms. It estimates the electric field from the bipolar electrograms of a clique, under the assumption of locally plane and homogeneous propagation. The local electric field evolution over time describes a loop trajectory from which omnipolar signals in the propagation direction, substrate and propagation features, are derived. In this work, we propose substrate and conduction velocity mapping modalities based on a modified version of the omnipolar electrogram method, which aims to reduce orientation-dependent residual components in the standard approach. Methods: A simulated electrical propagation in 2D, with a tissue including a circular patch of diffuse fibrosis, was used for validation. Unipolar electrograms were calculated in a multi-electrode array, also deriving bipolar electrograms along the two main directions of the grid. Simulated bipolar electrograms were also contaminated with real noise, to assess the robustness of the mapping strategies against noise. The performance of the maps in identifying fibrosis and in reproducing unipolar reference voltage maps was evaluated. Bipolar voltage maps were also considered for performance comparison. Results: Results show that the modified omnipolar mapping strategies are more accurate and robust against noise than bipolar and standard omnipolar maps in fibrosis detection (accuracies higher than 85 vs. 80% and 70%, respectively). They present better correlation with unipolar reference voltage maps than bipolar and original omnipolar maps (Pearson's correlations higher than 0.75 vs. 0.60 and 0.70, respectively). Conclusion: The modified omnipolar method improves fibrosis detection, characterization of substrate and propagation, also reducing the residual sensitivity to directionality over the standard approach and improving robustness against noise. Nevertheless, studies with real electrograms will elucidate its impact in catheter ablation interventions.
Collapse
Affiliation(s)
- Jennifer Riccio
- Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain
| | - Alejandro Alcaine
- Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain
- Facultad de Ciencias de la Salud, Universidad San Jorge, Zaragoza, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain
| | - Sara Rocher
- Centro de Investigación e Innovación en Ingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Laura Martinez-Mateu
- Departamento de Teoría de la Señal y Comunicaciones y Sistemas Telemáticos y Computación, Universidad Rey Juan Carlos, Madrid, Spain
| | - Sergio Laranjo
- Department of Pediatric Cardiology, Hospital Santa Marta, Centro Hospitalar de Lisboa Central, Lisbon, Portugal
| | - Javier Saiz
- Centro de Investigación e Innovación en Ingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain
| | - Juan Pablo Martínez
- Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain
| |
Collapse
|
15
|
Abstract
Computer modeling of the electrophysiology of the heart has undergone significant progress. A healthy heart can be modeled starting from the ion channels via the spread of a depolarization wave on a realistic geometry of the human heart up to the potentials on the body surface and the ECG. Research is advancing regarding modeling diseases of the heart. This article reviews progress in calculating and analyzing the corresponding electrocardiogram (ECG) from simulated depolarization and repolarization waves. First, we describe modeling of the P-wave, the QRS complex and the T-wave of a healthy heart. Then, both the modeling and the corresponding ECGs of several important diseases and arrhythmias are delineated: ischemia and infarction, ectopic beats and extrasystoles, ventricular tachycardia, bundle branch blocks, atrial tachycardia, flutter and fibrillation, genetic diseases and channelopathies, imbalance of electrolytes and drug-induced changes. Finally, we outline the potential impact of computer modeling on ECG interpretation. Computer modeling can contribute to a better comprehension of the relation between features in the ECG and the underlying cardiac condition and disease. It can pave the way for a quantitative analysis of the ECG and can support the cardiologist in identifying events or non-invasively localizing diseased areas. Finally, it can deliver very large databases of reliably labeled ECGs as training data for machine learning.
Collapse
|
16
|
Nakano Y, Rashed EA, Nakane T, Laakso I, Hirata A. ECG Localization Method Based on Volume Conductor Model and Kalman Filtering. SENSORS (BASEL, SWITZERLAND) 2021; 21:4275. [PMID: 34206512 PMCID: PMC8271910 DOI: 10.3390/s21134275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/15/2021] [Accepted: 06/17/2021] [Indexed: 11/24/2022]
Abstract
The 12-lead electrocardiogram was invented more than 100 years ago and is still used as an essential tool in the early detection of heart disease. By estimating the time-varying source of the electrical activity from the potential changes, several types of heart disease can be noninvasively identified. However, most previous studies are based on signal processing, and thus an approach that includes physics modeling would be helpful for source localization problems. This study proposes a localization method for cardiac sources by combining an electrical analysis with a volume conductor model of the human body as a forward problem and a sparse reconstruction method as an inverse problem. Our formulation estimates not only the current source location but also the current direction. For a 12-lead electrocardiogram system, a sensitivity analysis of the localization to cardiac volume, tilted angle, and model inhomogeneity was evaluated. Finally, the estimated source location is corrected by Kalman filter, considering the estimated electrocardiogram source as time-sequence data. For a high signal-to-noise ratio (greater than 20 dB), the dominant error sources were the model inhomogeneity, which is mainly attributable to the high conductivity of the blood in the heart. The average localization error of the electric dipole sources in the heart was 12.6 mm, which is comparable to that in previous studies, where a less detailed anatomical structure was considered. A time-series source localization with Kalman filtering indicated that source mislocalization could be compensated, suggesting the effectiveness of the source estimation using the current direction and location simultaneously. For the electrocardiogram R-wave, the mean distance error was reduced to less than 7.3 mm using the proposed method. Considering the physical properties of the human body with Kalman filtering enables highly accurate estimation of the cardiac electric signal source location and direction. This proposal is also applicable to electrode configuration, such as ECG sensing systems.
Collapse
Affiliation(s)
- Yuki Nakano
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (Y.N.); (E.A.R.); (T.N.)
| | - Essam A. Rashed
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (Y.N.); (E.A.R.); (T.N.)
- Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt
| | - Tatsuhito Nakane
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (Y.N.); (E.A.R.); (T.N.)
| | - Ilkka Laakso
- Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland;
| | - Akimasa Hirata
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (Y.N.); (E.A.R.); (T.N.)
- Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan
| |
Collapse
|
17
|
Ushenin K, Kalinin V, Gitinova S, Sopov O, Solovyova O. Parameter variations in personalized electrophysiological models of human heart ventricles. PLoS One 2021; 16:e0249062. [PMID: 33909606 PMCID: PMC8081243 DOI: 10.1371/journal.pone.0249062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 03/10/2021] [Indexed: 11/18/2022] Open
Abstract
The objectives of this study were to evaluate the accuracy of personalized numerical simulations of the electrical activity in human ventricles by comparing simulated electrocardiograms (ECGs) with real patients’ ECGs and analyzing the sensitivity of the model output to variations in the model parameters. We used standard 12-lead ECGs and up to 224 unipolar body-surface ECGs to record three patients with cardiac resynchronization therapy devices and three patients with focal ventricular tachycardia. Patient-tailored geometrical models of the ventricles, atria, large vessels, liver, and spine were created using computed tomography data. Ten cases of focal ventricular activation were simulated using the bidomain model and the TNNP 2006 cellular model. The population-based values of electrical conductivities and other model parameters were used for accuracy analysis, and their variations were used for sensitivity analysis. The mean correlation coefficient between the simulated and real ECGs varied significantly (from r = 0.29 to r = 0.86) among the simulated cases. A strong mean correlation (r > 0.7) was found in eight of the ten model cases. The accuracy of the ECG simulation varied widely in the same patient depending on the localization of the excitation origin. The sensitivity analysis revealed that variations in the anisotropy ratio, blood conductivity, and cellular apicobasal heterogeneity had the strongest influence on transmembrane potential, while variation in lung conductivity had the greatest influence on body-surface ECGs. Futhermore, the anisotropy ratio predominantly affected the latest activation time and repolarization time dispersion, while the cellular apicobasal heterogeneity mainly affected the dispersion of action potential duration, and variation in lung conductivity mainly led to changes in the amplitudes of ECGs and cardiac electrograms. We also found that the effects of certain parameter variations had specific regional patterns on the cardiac and body surfaces. These observations are useful for further developing personalized cardiac models.
Collapse
Affiliation(s)
- Konstantin Ushenin
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg, Russia
- Institute of Immunology and Physiology of the Ural Branch of the RAS, Ekaterinburg, Russia
- * E-mail:
| | | | - Sukaynat Gitinova
- Department of Surgical Treatment of Tachyarrhythmias, A.N. Bakulev National Medical Research Center of Cardiovascular Surgery, Moscow, Russia
| | - Oleg Sopov
- Department of Surgical Treatment of Tachyarrhythmias, A.N. Bakulev National Medical Research Center of Cardiovascular Surgery, Moscow, Russia
| | - Olga Solovyova
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg, Russia
- Institute of Immunology and Physiology of the Ural Branch of the RAS, Ekaterinburg, Russia
| |
Collapse
|
18
|
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs. Med Image Anal 2021; 71:102080. [PMID: 33975097 DOI: 10.1016/j.media.2021.102080] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/15/2021] [Accepted: 04/06/2021] [Indexed: 12/21/2022]
Abstract
Cardiac digital twins (Cardiac Digital Twin (CDT)s) of human electrophysiology (Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that match like-for-like all available clinical observations. Due to their inherent predictive potential, CDTs show high promise as a complementary modality aiding in clinical decision making and also in the cost-effective, safe and ethical testing of novel EP device therapies. However, current workflows for both the anatomical and functional twinning phases within CDT generation, referring to the inference of model anatomy and parameters from clinical data, are not sufficiently efficient, robust and accurate for advanced clinical and industrial applications. Our study addresses three primary limitations impeding the routine generation of high-fidelity CDTs by introducing; a comprehensive parameter vector encapsulating all factors relating to the ventricular EP; an abstract reference frame within the model allowing the unattended manipulation of model parameter fields; a novel fast-forward electrocardiogram (Electrocardiogram (ECG)) model for efficient and bio-physically-detailed simulation required for parameter inference. A novel workflow for the generation of CDTs is then introduced as an initial proof of concept. Anatomical twinning was performed within a reasonable time compatible with clinical workflows (<4h) for 12 subjects from clinically-attained magnetic resonance images. After assessment of the underlying fast forward ECG model against a gold standard bidomain ECG model, functional twinning of optimal parameters according to a clinically-attained 12 lead ECG was then performed using a forward Saltelli sampling approach for a single subject. The achieved results in terms of efficiency and fidelity demonstrate that our workflow is well-suited and viable for generating biophysically-detailed CDTs at scale.
Collapse
|
19
|
Abstract
The capability of magnetic induction to transmit signals in attenuating environments has recently gained significant research interest. The wave aspect—magnetoinductive (MI) waves—has been proposed for numerous applications in RF-challenging environments, such as underground/underwater wireless networks, body area networks, and in-vivo medical diagnosis and treatment applications, to name but a few, where conventional electromagnetic waves have a number of limitations, most notably losses. To date, the effects of eddy currents inside the dissipative medium have not been characterised analytically. Here we propose a comprehensive circuit model of coupled resonators in a homogeneous dissipative medium, that takes into account all the electromagnetic effects of eddy currents, and, thereby, derive a general dispersion equation for the MI waves. We also report laboratory experiments to confirm our findings. Our work will serve as a fundamental model for design and analysis of every system employing MI waves or more generally, magnetically-coupled circuits in attenuating media.
Collapse
|
20
|
Campos FO, Orini M, Arnold R, Whitaker J, O'Neill M, Razavi R, Plank G, Hanson B, Porter B, Rinaldi CA, Gill J, Lambiase PD, Taggart P, Bishop MJ. Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling. Comput Biol Med 2021; 130:104214. [PMID: 33476992 DOI: 10.1016/j.compbiomed.2021.104214] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 01/05/2021] [Accepted: 01/05/2021] [Indexed: 01/19/2023]
Abstract
BACKGROUND Identification of targets for ablation of post-infarction ventricular tachycardias (VTs) remains challenging, often requiring arrhythmia induction to delineate the reentrant circuit. This carries a risk for the patient and may not be feasible. Substrate mapping has emerged as a safer strategy to uncover arrhythmogenic regions. However, VT recurrence remains common. GOAL To use computer simulations to assess the ability of different substrate mapping approaches to identify VT exit sites. METHODS A 3D computational model of the porcine post-infarction heart was constructed to simulate VT and paced rhythm. Electroanatomical maps were constructed based on endocardial electrogram features and the reentry vulnerability index (RVI - a metric combining activation (AT) and repolarization timings to identify tissue susceptibility to reentry). Since scar transmurality in our model was not homogeneous, parameters derived from all signals (including dense scar regions) were used in the analysis. Potential ablation targets obtained from each electroanatomical map during pacing were compared to the exit site detected during VT mapping. RESULTS Simulation data showed that voltage cut-offs applied to bipolar electrograms could delineate the scar, but not the VT circuit. Electrogram fractionation had the highest correlation with scar transmurality. The RVI identified regions closest to VT exit site but was outperformed by AT gradients combined with voltage cut-offs. The performance of all metrics was affected by pacing location. CONCLUSIONS Substrate mapping could provide information about the infarct, but the directional dependency on activation should be considered. Activation-repolarization metrics have utility in safely identifying VT targets, even with non-transmural scars.
Collapse
Affiliation(s)
- Fernando O Campos
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom.
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Electrophysiology Department, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Robert Arnold
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Division of Biophysics, Graz, Austria
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom
| | - Mark O'Neill
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom
| | - Gernot Plank
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Division of Biophysics, Graz, Austria
| | - Ben Hanson
- Department of Mechanical Engineering, University College London, London, United Kingdom
| | - Bradley Porter
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom; Department of Cardiology, Guys and St Thomas' NHS Trust, London, United Kingdom
| | | | - Jaswinder Gill
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom; Department of Cardiology, Guys and St Thomas' NHS Trust, London, United Kingdom
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Electrophysiology Department, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Peter Taggart
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Electrophysiology Department, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Martin J Bishop
- School of Biomedical Engineering and Imaging Sciences, Rayne Institute, 4th Floor, Lambeth Wing, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, United Kingdom
| |
Collapse
|
21
|
Approaches for determining cardiac bidomain conductivity values: progress and challenges. Med Biol Eng Comput 2020; 58:2919-2935. [PMID: 33089458 DOI: 10.1007/s11517-020-02272-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 09/17/2020] [Indexed: 10/23/2022]
Abstract
Modelling the electrical activity of the heart is an important tool for understanding electrical function in various diseases and conduction disorders. Clearly, for model results to be useful, it is necessary to have accurate inputs for the models, in particular the commonly used bidomain model. However, there are only three sets of four experimentally determined conductivity values for cardiac ventricular tissue and these are inconsistent, were measured around 40 years ago, often produce different results in simulations and do not fully represent the three-dimensional anisotropic nature of cardiac tissue. Despite efforts in the intervening years, difficulties associated with making the measurements and also determining the conductivities from the experimental data have not yet been overcome. In this review, we summarise what is known about the conductivity values, as well as progress to date in meeting the challenges associated with both the mathematical modelling and the experimental techniques. Graphical abstract Epicardial potential distributions, arising from a subendocardial ischaemic region, modelled using conductivity data from the indicated studies.
Collapse
|
22
|
van der Waal J, Meijborg V, Schuler S, Coronel R, Oostendorp T. In silico validation of electrocardiographic imaging to reconstruct the endocardial and epicardial repolarization pattern using the equivalent dipole layer source model. Med Biol Eng Comput 2020; 58:1739-1749. [PMID: 32474796 PMCID: PMC7340677 DOI: 10.1007/s11517-020-02203-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 05/22/2020] [Indexed: 02/07/2023]
Abstract
The solution of the inverse problem of electrocardiology allows the reconstruction of the spatial distribution of the electrical activity of the heart from the body surface electrocardiogram (electrocardiographic imaging, ECGI). ECGI using the equivalent dipole layer (EDL) model has shown to be accurate for cardiac activation times. However, validation of this method to determine repolarization times is lacking. In the present study, we determined the accuracy of the EDL model in reconstructing cardiac repolarization times, and assessed the robustness of the method under less ideal conditions (addition of noise and errors in tissue conductivity). A monodomain model was used to determine the transmembrane potentials in three different excitation-repolarization patterns (sinus beat and ventricular ectopic beats) as the gold standard. These were used to calculate the body surface ECGs using a finite element model. The resulting body surface electrograms (ECGs) were used as input for the EDL-based inverse reconstruction of repolarization times. The reconstructed repolarization times correlated well (COR > 0.85) with the gold standard, with almost no decrease in correlation after adding errors in tissue conductivity of the model or noise to the body surface ECG. Therefore, ECGI using the EDL model allows adequate reconstruction of cardiac repolarization times. Graphical abstract Validation of electrocardiographic imaging for repolarization using forward calculated body surface ECGs from simulated activation-repolarization sequences.
Collapse
Affiliation(s)
- Jeanne van der Waal
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands.
| | - Veronique Meijborg
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Fritz-Haber-Weg 1, 76131, Karlsruhe, Germany
| | - Ruben Coronel
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Thom Oostendorp
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Kapittelweg 29, 6525, Nijmegen, The Netherlands
| |
Collapse
|
23
|
Segmentation of Abdominal Computed Tomography Scans Using Analysis of Texture Features and Its Application to Personalized Forward Electrocardiography Modeling. ACTA ACUST UNITED AC 2019. [DOI: 10.1007/978-3-030-23436-2_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
|
24
|
Mincholé A, Zacur E, Ariga R, Grau V, Rodriguez B. MRI-Based Computational Torso/Biventricular Multiscale Models to Investigate the Impact of Anatomical Variability on the ECG QRS Complex. Front Physiol 2019; 10:1103. [PMID: 31507458 PMCID: PMC6718559 DOI: 10.3389/fphys.2019.01103] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 08/08/2019] [Indexed: 01/07/2023] Open
Abstract
AIMS Patient-to-patient anatomical differences are an important source of variability in the electrocardiogram, and they may compromise the identification of pathological electrophysiological abnormalities. This study aims at quantifying the contribution of variability in ventricular and torso anatomies to differences in QRS complexes of the 12-lead ECG using computer simulations. METHODS A computational pipeline is presented that enables computer simulations using human torso/biventricular anatomically based electrophysiological models from clinically standard magnetic resonance imaging (MRI). The ventricular model includes membrane kinetics represented by the biophysically detailed O'Hara Rudy model modified for tissue heterogeneity and includes fiber orientation based on the Streeter rule. A population of 265 torso/biventricular models was generated by combining ventricular and torso anatomies obtained from clinically standard MRIs, augmented with a statistical shape model of the body. 12-lead ECGs were simulated on the 265 human torso/biventricular electrophysiology models, and QRS morphology, duration and amplitude were quantified in each ECG lead for each of the human torso-biventricular models. RESULTS QRS morphologies in limb leads are mainly determined by ventricular anatomy, while in the precordial leads, and especially V1 to V4, they are determined by heart position within the torso. Differences in ventricular orientation within the torso can explain morphological variability from monophasic to biphasic QRS complexes. QRS duration is mainly influenced by myocardial volume, while it is hardly affected by the torso anatomy or position. An average increase of 0.12 ± 0.05 ms in QRS duration is obtained for each cm3 of myocardial volume across all the leads while it hardly changed due to changes in torso volume. CONCLUSION Computer simulations using populations of human torso/biventricular models based on clinical MRI enable quantification of anatomical causes of variability in the QRS complex of the 12-lead ECG. The human models presented also pave the way toward their use as testbeds in silico clinical trials.
Collapse
Affiliation(s)
- Ana Mincholé
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Ernesto Zacur
- Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, United Kingdom
| | - Rina Ariga
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Vicente Grau
- Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
25
|
Lopez-Perez A, Sebastian R, Izquierdo M, Ruiz R, Bishop M, Ferrero JM. Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia. Front Physiol 2019; 10:580. [PMID: 31156460 PMCID: PMC6531915 DOI: 10.3389/fphys.2019.00580] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 04/25/2019] [Indexed: 12/20/2022] Open
Abstract
In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this strategy show relatively low success rates; up to 50% of patients experience recurrent VT after the procedure. In the last decade, intensive research in the field of computational cardiac electrophysiology (EP) has demonstrated the ability of three-dimensional (3D) cardiac computational models to perform in-silico EP studies. However, the personalization and modeling of certain key components remain challenging, particularly in the case of the infarct border zone (BZ). In this study, we used a clinical dataset from a patient with a history of infarct-related VT to build an image-based 3D ventricular model aimed at computational simulation of cardiac EP, including detailed patient-specific cardiac anatomy and infarct scar geometry. We modeled the BZ in eight different ways by combining the presence or absence of electrical remodeling with four different levels of image-based patchy fibrosis (0, 10, 20, and 30%). A 3D torso model was also constructed to compute the ECG. Patient-specific sinus activation patterns were simulated and validated against the patient's ECG. Subsequently, the pacing protocol used to induce reentrant VTs in the EP laboratory was reproduced in-silico. The clinical VT was induced with different versions of the model and from different pacing points, thus identifying the slow conducting channel responsible for such VT. Finally, the real patient's ECG recorded during VT episodes was used to validate our simulation results and to assess different strategies to model the BZ. Our study showed that reduced conduction velocities and heterogeneity in action potential duration in the BZ are the main factors in promoting reentrant activity. Either electrical remodeling or fibrosis in a degree of at least 30% in the BZ were required to initiate VT. Moreover, this proof-of-concept study confirms the feasibility of developing 3D computational models for cardiac EP able to reproduce cardiac activation in sinus rhythm and during VT, using exclusively non-invasive clinical data.
Collapse
Affiliation(s)
- Alejandro Lopez-Perez
- Center for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Simulation Lab (CoMMLab), Universitat de València, Valencia, Spain
| | - M Izquierdo
- INCLIVA Health Research Institute, Valencia, Spain.,Arrhythmia Unit, Cardiology Department, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Ricardo Ruiz
- INCLIVA Health Research Institute, Valencia, Spain.,Arrhythmia Unit, Cardiology Department, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Martin Bishop
- Division of Imaging Sciences & Biomedical Engineering, Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Jose M Ferrero
- Center for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| |
Collapse
|
26
|
Martinez-Mateu L, Romero L, Saiz J, Berenfeld O. Far-field contributions in multi-electrodes atrial recordings blur distinction between anatomical and functional reentries and may cause imaginary phase singularities - A computational study. Comput Biol Med 2019; 108:276-287. [PMID: 31015048 DOI: 10.1016/j.compbiomed.2019.02.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 02/14/2019] [Accepted: 02/21/2019] [Indexed: 01/11/2023]
Abstract
BACKGROUND Atrial fibrillation (AF) is the most common cardiac arrhythmia and the most important cause of embolic stroke, requiring new technologies for its better understanding and therapies. Recent approaches to map the electrical activity during AF with multi-electrode systems aim at localizing patient-specific ablation targets of reentrant patterns. However, there is a critical need to determine the accuracy of those mapping systems. We performed computer simulations as a numerical approach of systematically evaluating the influence of far-field sources on the electrical recordings and detection of rotors. METHODS We constructed 2 computer models of atrial tissue: (i) a 2D sheet model with varying non-active cells area in its center, and (ii) a whole realistic 3D atrial model. Phase maps were built based on the Hilbert transform of the unipolar electrograms recorded by virtual 2D and 3D multi-electrode systems and rotors were tracked through phase singularities detections. RESULTS Analysis of electrograms recorded away from the 2D atrial model shows that the larger the distance between an electrode and the tissue model, the stronger the far-field sources contribution to the electrogram is. Importantly, even if an electrode is positioned in contact with the tissue, the electrogram contains significant contributions from distal sources that blur the distinction between anatomical and functional reentries. Moreover, when mapping the 3D atrial model, remote activity generated false phase singularities at locations without local reentrant excitation patterns. CONCLUSIONS Far-field contributions to electrograms during AF reduce the accuracy of detecting and interpreting reentrant activity.
Collapse
Affiliation(s)
- Laura Martinez-Mateu
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain.
| | - Lucia Romero
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI, USA
| |
Collapse
|
27
|
Carpio EF, Gomez JF, Sebastian R, Lopez-Perez A, Castellanos E, Almendral J, Ferrero JM, Trenor B. Optimization of Lead Placement in the Right Ventricle During Cardiac Resynchronization Therapy. A Simulation Study. Front Physiol 2019; 10:74. [PMID: 30804805 PMCID: PMC6378298 DOI: 10.3389/fphys.2019.00074] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Accepted: 01/22/2019] [Indexed: 12/18/2022] Open
Abstract
Patients suffering from heart failure and left bundle branch block show electrical ventricular dyssynchrony causing an abnormal blood pumping. Cardiac resynchronization therapy (CRT) is recommended for these patients. Patients with positive therapy response normally present QRS shortening and an increased left ventricle (LV) ejection fraction. However, around one third do not respond favorably. Therefore, optimal location of pacing leads, timing delays between leads and/or choosing related biomarkers is crucial to achieve the best possible degree of ventricular synchrony during CRT application. In this study, computational modeling is used to predict the optimal location and delay of pacing leads to improve CRT response. We use a 3D electrophysiological computational model of the heart and torso to get insight into the changes in the activation patterns obtained when the heart is paced from different regions and for different atrioventricular and interventricular delays. The model represents a heart with left bundle branch block and heart failure, and allows a detailed and accurate analysis of the electrical changes observed simultaneously in the myocardium and in the QRS complex computed in the precordial leads. Computational simulations were performed using a modified version of the O'Hara et al. action potential model, the most recent mathematical model developed for human ventricular electrophysiology. The optimal location for the pacing leads was determined by QRS maximal reduction. Additionally, the influence of Purkinje system on CRT response was assessed and correlation analysis between several parameters of the QRS was made. Simulation results showed that the right ventricle (RV) upper septum near the outflow tract is an alternative location to the RV apical lead. Furthermore, LV endocardial pacing provided better results as compared to epicardial stimulation. Finally, the time to reach the 90% of the QRS area was a good predictor of the instant at which 90% of the ventricular tissue was activated. Thus, the time to reach the 90% of the QRS area is suggested as an additional index to assess CRT effectiveness to improve biventricular synchrony.
Collapse
Affiliation(s)
- Edison F Carpio
- Centre for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Juan F Gomez
- Centre for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Simulation Lab (CoMMLab), Department of Computer Science, Universitat de València, Valencia, Spain
| | - Alejandro Lopez-Perez
- Centre for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Eduardo Castellanos
- Electrophysiology Laboratory and Arrhythmia Unit, Grupo HM Hospitales, Hospital Monteprincipe, University CEU-San Pablo, Madrid, Spain
| | - Jesus Almendral
- Electrophysiology Laboratory and Arrhythmia Unit, Grupo HM Hospitales, Hospital Monteprincipe, University CEU-San Pablo, Madrid, Spain
| | - Jose M Ferrero
- Centre for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Beatriz Trenor
- Centre for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València, Valencia, Spain
| |
Collapse
|
28
|
Godoy EJ, Lozano M, García-Fernández I, Ferrer-Albero A, MacLeod R, Saiz J, Sebastian R. Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study. Front Physiol 2018; 9:404. [PMID: 29867517 PMCID: PMC5968126 DOI: 10.3389/fphys.2018.00404] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 04/04/2018] [Indexed: 12/13/2022] Open
Abstract
Introduction: Focal atrial tachycardia is commonly treated by radio frequency ablation with an acceptable long-term success. Although the location of ectopic foci tends to appear in specific hot-spots, they can be located virtually in any atrial region. Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for non-invasive therapy planning of cardiac arrhythmia. However, the activation of the atria could be affected by fibrosis and therefore biomarkers based on BSPM need to take these effects into account. We aim to analyze the effect of fibrosis on a BSPM derived index, and its potential application to predict the location of ectopic foci in the atria. Methodology: We have developed a 3D atrial model that includes 5 distributions of patchy fibrosis in the left atrium at 5 different stages. Each stage corresponds to a different amount of fibrosis that ranges from 2 to 40%. The 25 resulting 3D models were used for simulation of Focal Atrial Tachycardia (FAT), triggered from 19 different locations described in clinical studies. BSPM were obtained for all simulations, and the body surface potential integral maps (BSPiM) were calculated to describe atrial activations. A machine learning (ML) pipeline using a supervised learning model and support vector machine was developed to learn the BSPM patterns of each of the 475 activation sequences and relate them to the origin of the FAT source. Results: Activation maps for stages with more than 15% of fibrosis were greatly affected, producing conduction blocks and delays in propagation. BSPiMs did not always cluster into non-overlapped groups since BSPiMs were highly altered by the conduction blocks. From stage 3 (15% fibrosis) the BSPiMs showed differences for ectopic beats placed around the area of the pulmonary veins. Classification results were mostly above 84% for all the configurations studied when a large enough number of electrodes were used to map the torso. However, the presence of fibrosis increases the area of the ectopic focus location and therefore decreases the utility for the electrophysiologist. Conclusions: The results indicate that the proposed ML pipeline is a promising methodology for non-invasive ectopic foci localization from BSPM signal even when fibrosis is present.
Collapse
Affiliation(s)
- Eduardo Jorge Godoy
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Miguel Lozano
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Ignacio García-Fernández
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Ana Ferrer-Albero
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Rob MacLeod
- Department of Bioengineering, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | - Javier Saiz
- Centro de Investigación en Bioingeniería, Universitat Politécnica de Valencia, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de Valencia, Valencia, Spain
| |
Collapse
|
29
|
Janssen AM, Potyagaylo D, Dössel O, Oostendorp TF. Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart. Med Biol Eng Comput 2018. [PMID: 29130137 DOI: 10.1007/sll517-017-1715-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.
Collapse
Affiliation(s)
- Arno M Janssen
- The Netherlands Heart Institute, Utrecht, The Netherlands
- The Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Danila Potyagaylo
- The Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Olaf Dössel
- The Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Thom F Oostendorp
- The Netherlands Heart Institute, Utrecht, The Netherlands
- The Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| |
Collapse
|
30
|
Potse M. Scalable and Accurate ECG Simulation for Reaction-Diffusion Models of the Human Heart. Front Physiol 2018; 9:370. [PMID: 29731720 PMCID: PMC5920200 DOI: 10.3389/fphys.2018.00370] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 03/27/2018] [Indexed: 11/13/2022] Open
Abstract
Realistic electrocardiogram (ECG) simulation with numerical models is important for research linking cellular and molecular physiology to clinically observable signals, and crucial for patient tailoring of numerical heart models. However, ECG simulation with a realistic torso model is computationally much harder than simulation of cardiac activity itself, so that many studies with sophisticated heart models have resorted to crude approximations of the ECG. This paper shows how the classical concept of electrocardiographic lead fields can be used for an ECG simulation method that matches the realism of modern heart models. The accuracy and resource requirements were compared to those of a full-torso solution for the potential and scaling was tested up to 14,336 cores with a heart model consisting of 11 million nodes. Reference ECGs were computed on a 3.3 billion-node heart-torso mesh at 0.2 mm resolution. The results show that the lead-field method is more efficient than a full-torso solution when the number of simulated samples is larger than the number of computed ECG leads. While the initial computation of the lead fields remains a hard and poorly scalable problem, the ECG computation itself scales almost perfectly and, even for several hundreds of ECG leads, takes much less time than the underlying simulation of cardiac activity.
Collapse
Affiliation(s)
- Mark Potse
- CARMEN Research Team, Inria Bordeaux Sud-Ouest, Talence, France.,Institut de Mathématiques de Bordeaux, UMR 5251, Université de Bordeaux, Talence, France.,IHU Liryc, Electrophysiology and Heart Modeling Institute, Foundation Bordeaux Université, Pessac-Bordeaux, France
| |
Collapse
|
31
|
Martinez-Mateu L, Romero L, Ferrer-Albero A, Sebastian R, Rodríguez Matas JF, Jalife J, Berenfeld O, Saiz J. Factors affecting basket catheter detection of real and phantom rotors in the atria: A computational study. PLoS Comput Biol 2018; 14:e1006017. [PMID: 29505583 PMCID: PMC5854439 DOI: 10.1371/journal.pcbi.1006017] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 03/15/2018] [Accepted: 02/01/2018] [Indexed: 02/07/2023] Open
Abstract
Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35-94% of the simulation time, depending on the basket's position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures.
Collapse
Affiliation(s)
- Laura Martinez-Mateu
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Lucia Romero
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Ana Ferrer-Albero
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Simulation Lab, Department of Computer Science, Universitat de València, Valencia, Spain
| | - José F. Rodríguez Matas
- Dipartimento di Chimica, Materiali e Ingegneria Chimica “Giulio Natta”, Politecnico di Milano, Milano, Italy
| | - José Jalife
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan, United States of America
- Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- CIBER of Cardiovascular Diseases, Madrid, Spain
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| |
Collapse
|
32
|
Rodrigo M, Climent AM, Liberos A, Hernandez-Romero I, Arenal A, Bermejo J, Fernandez-Aviles F, Atienza F, Guillem MS. Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:733-740. [PMID: 28541896 DOI: 10.1109/tmi.2017.2707413] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Electrocardiographic Imaging has become an increasingly used technique for non-invasive diagnosis of cardiac arrhythmias, although the need for medical imaging technology to determine the anatomy hinders its introduction in the clinical practice. This paper explores the ability of a new metric based on the inverse reconstruction quality for the location and orientation of the atrial surface inside the torso. Body surface electrical signals from 31 realistic mathematical models and four AF patients were used to estimate the optimal position of the atria inside the torso. The curvature of the L-curve from the Tikhonov method, which was found to be related to the inverse reconstruction quality, was measured after application of deviations in atrial position and orientation. Independent deviations in the atrial position were solved by finding the maximal L-curve curvature with an error of 1.7 ± 2.4 mm in mathematical models and 9.1 ± 11.5 mm in patients. For the case of independent angular deviations, the error in location by using the L-curve was 5.8±7.1° in mathematical models and 12.4° ± 13.2° in patients. The ability of the L-curve curvature was tested also under superimposed uncertainties in the three axis of translation and in the three axis of rotation, and the error in location was of 2.3 ± 3.2 mm and 6.4° ± 7.1° in mathematical models, and 7.9±10.7 mm and 12.1°±15.5° in patients. The curvature of L-curve is a useful marker for the atrial position and would allow emending the inaccuracies in its location.
Collapse
|
33
|
Van Nieuwenhuyse E, Seemann G, Panfilov AV, Vandersickel N. Effects of early afterdepolarizations on excitation patterns in an accurate model of the human ventricles. PLoS One 2017; 12:e0188867. [PMID: 29216239 PMCID: PMC5720514 DOI: 10.1371/journal.pone.0188867] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 11/14/2017] [Indexed: 12/17/2022] Open
Abstract
Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence prohibiting the Sodium channel gates to recover. Accordingly, we found that Calcium waves mediated these patterns. Third, a further reduction of the RR resulted in a more exotic parameter regime whereby the individual cells behaved independently as oscillators. The patterns arose due to a phase-shift of different oscillators as disconnection of the cells resulted in continuation of the patterns. For all patterns, we computed realistic 9 lead ECGs by including a torso model. The B and A type pattern exposed the behavior of Ventricular Tachycardia (VT). We conclude that EADs at the single cell level can result in different types of cardiac fibrillation at the tissue and 3D ventricle level.
Collapse
Affiliation(s)
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg, Bad Krozingen, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | | | - Nele Vandersickel
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| |
Collapse
|
34
|
Janssen AM, Potyagaylo D, Dössel O, Oostendorp TF. Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart. Med Biol Eng Comput 2017; 56:1013-1025. [PMID: 29130137 PMCID: PMC5978848 DOI: 10.1007/s11517-017-1715-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Accepted: 08/17/2017] [Indexed: 12/25/2022]
Abstract
Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.
Collapse
Affiliation(s)
- Arno M Janssen
- The Netherlands Heart Institute, Utrecht, The Netherlands.,The Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Danila Potyagaylo
- The Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Olaf Dössel
- The Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Thom F Oostendorp
- The Netherlands Heart Institute, Utrecht, The Netherlands.,The Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| |
Collapse
|
35
|
Sánchez C, D'Ambrosio G, Maffessanti F, Caiani EG, Prinzen FW, Krause R, Auricchio A, Potse M. Sensitivity analysis of ventricular activation and electrocardiogram in tailored models of heart-failure patients. Med Biol Eng Comput 2017; 56:491-504. [PMID: 28823052 DOI: 10.1007/s11517-017-1696-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 07/20/2017] [Indexed: 01/13/2023]
Abstract
Cardiac resynchronization therapy is not effective in a variable proportion of heart failure patients. An accurate knowledge of each patient's electroanatomical features could be helpful to determine the most appropriate treatment. The goal of this study was to analyze and quantify the sensitivity of left ventricular (LV) activation and the electrocardiogram (ECG) to changes in 39 parameters used to tune realistic anatomical-electrophysiological models of the heart. Electrical activity in the ventricles was simulated using a reaction-diffusion equation. To simulate cellular electrophysiology, the Ten Tusscher-Panfilov 2006 model was used. Intracardiac electrograms and 12-lead ECGs were computed by solving the bidomain equation. Parameters showing the highest sensitivity values were similar in the six patients studied. QRS complex and LV activation times were modulated by the sodium current, the cell surface-to-volume ratio in the LV, and tissue conductivities. The T-wave was modulated by the calcium and rectifier-potassium currents, and the cell surface-to-volume ratio in both ventricles. We conclude that homogeneous changes in ionic currents entail similar effects in all ECG leads, whereas the effects of changes in tissue properties show larger inter-lead variability. The effects of parameter variations are highly consistent between patients and most of the model tuning could be performed with only ~10 parameters.
Collapse
Affiliation(s)
- C Sánchez
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland.
- General Military Academy of Zaragoza (AGM), Defense University Centre (CUD), Zaragoza, Spain.
- Present address: Biosignal Interpretation and Computational Simulation Group (BSICoS), Engineering Research Institute of Aragon (I3A), University of Zaragoza, Zaragoza, Spain.
| | - G D'Ambrosio
- Division of Cardiology, Cardiocentro Ticino, Lugano, Switzerland
| | - F Maffessanti
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
| | - E G Caiani
- Electronics, Information, and Bioengineering Department, Politecnico di Milano, Milan, Italy
| | - F W Prinzen
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
| | - R Krause
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
| | - A Auricchio
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
- Division of Cardiology, Cardiocentro Ticino, Lugano, Switzerland
| | - M Potse
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
- IHU LIRYC, Université de Bordeaux, Pessac, France
- Inria Bordeaux Sud-Ouest, Talence, France
| |
Collapse
|
36
|
Cardone-Noott L, Bueno-Orovio A, Mincholé A, Zemzemi N, Rodriguez B. Human ventricular activation sequence and the simulation of the electrocardiographic QRS complex and its variability in healthy and intraventricular block conditions. Europace 2017; 18:iv4-iv15. [PMID: 28011826 PMCID: PMC5225966 DOI: 10.1093/europace/euw346] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Accepted: 08/09/2016] [Indexed: 12/01/2022] Open
Abstract
Aims To investigate how variability in activation sequence and passive conduction properties translates into clinical variability in QRS biomarkers, and gain novel physiological knowledge on the information contained in the human QRS complex. Methods and results Multiscale bidomain simulations using a detailed heart-torso human anatomical model are performed to investigate the impact of activation sequence characteristics on clinical QRS biomarkers. Activation sequences are built and validated against experimentally-derived ex vivo and in vivo human activation data. R-peak amplitude exhibits the largest variability in terms of QRS morphology, due to its simultaneous modulation by activation sequence speed, myocardial intracellular and extracellular conductivities, and propagation through the human torso. QRS width, however, is regulated by endocardial activation speed and intracellular myocardial conductivities, whereas QR intervals are only affected by the endocardial activation profile. Variability in the apico-basal location of activation sites on the anterior and posterior left ventricular wall is associated with S-wave progression in limb and precordial leads, respectively, and occasional notched QRS complexes in precordial derivations. Variability in the number of early activation sites successfully reproduces pathological abnormalities of the human conduction system in the QRS complex. Conclusion Variability in activation sequence and passive conduction properties captures and explains a large part of the clinical variability observed in the human QRS complex. Our physiological insights allow for a deeper interpretation of human QRS biomarkers in terms of QRS morphology and location of early endocardial activation sites. This might be used to attain a better patient-specific knowledge of activation sequence from routine body-surface electrocardiograms.
Collapse
Affiliation(s)
- Louie Cardone-Noott
- Department of Computer Science and British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford OX1 3QD, UK
| | - Alfonso Bueno-Orovio
- Department of Computer Science and British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford OX1 3QD, UK
| | - Ana Mincholé
- Department of Computer Science and British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford OX1 3QD, UK
| | - Nejib Zemzemi
- INRIA Bordeaux Sud-Ouest, 200 avenue de la vieille tour, Talence Cedex 33405, France.,IHU Liryc, Electrophysiology and Heart Modeling Institute, foundation Bordeaux Université, F-33600 Pessac Bordeaux, France
| | - Blanca Rodriguez
- Department of Computer Science and British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford OX1 3QD, UK
| |
Collapse
|
37
|
Ferrer-Albero A, Godoy EJ, Lozano M, Martínez-Mateu L, Atienza F, Saiz J, Sebastian R. Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps. PLoS One 2017; 12:e0181263. [PMID: 28704537 PMCID: PMC5509320 DOI: 10.1371/journal.pone.0181263] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 06/28/2017] [Indexed: 01/22/2023] Open
Abstract
Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly differentiated atrial regions by using the body surface P-wave integral map (BSPiM) as a biomarker. Our simulated results show that ectopic foci with similar BSPiM naturally cluster into differentiated non-intersected atrial regions and that new patterns could be correctly classified with an accuracy of 97% when considering 2 clusters and 96% for 4 clusters. Our results also suggest that an increase in the number of clusters is feasible at the cost of decreasing accuracy.
Collapse
Affiliation(s)
- Ana Ferrer-Albero
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
- * E-mail:
| | - Eduardo J. Godoy
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Miguel Lozano
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Laura Martínez-Mateu
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | | | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| |
Collapse
|
38
|
Oosterhoff P, Meijborg VMF, van Dam PM, van Dessel PFHM, Belterman CNW, Streekstra GJ, de Bakker JMT, Coronel R, Oostendorp TF. Experimental Validation of Noninvasive Epicardial and Endocardial Activation Imaging. Circ Arrhythm Electrophysiol 2017; 9:e004104. [PMID: 27439651 DOI: 10.1161/circep.116.004104] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 06/20/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND Noninvasive imaging of cardiac activation before ablation of the arrhythmogenic substrate can reduce electrophysiological procedure duration and help choosing between an endocardial or epicardial approach. A noninvasive imaging technique was evaluated that estimates both endocardial and epicardial activation from body surface potential maps. We performed a study in isolated and in situ pig hearts, estimating activation from body surface potential maps during sinus rhythm and localizing endocardial and epicardial stimulation sites. METHODS AND RESULTS From 3 Langendorff-perfused pig hearts, 180 intramural unipolar electrograms were recorded during sinus rhythm and ectopic activation, together with pseudo-body surface potential map ECGs in 2 of them. From 4 other anesthetized pigs, 64-lead body surface potential maps were recorded during sinus rhythm and ventricular stimulation from 27 endocardial and epicardial sites. The ventricular activation pattern was computed from the recorded QRS complexes. For both Langendorff-perfused hearts, the calculated epicardial and endocardial activation patterns showed good qualitative correspondence to the patterns obtained with needle electrodes. Absolute timing difference for sinus rhythm was 10±5 and 11±8 ms respectively, and for ectopic activation 6±5 and 7±6 ms, respectively. Calculated activation for the in situ hearts in sinus rhythm was similar to patterns recorded in Langendorff-perfused hearts. During stimulation, the distance between the stimulation site and calculated site of earliest activation was 18 (15-27) mm, and 23 of 27 stimulation sites were correctly mapped to either endocardium or epicardium. CONCLUSIONS Noninvasive activation imaging is able to determine earliest ventricular activation and discriminate endocardial from epicardial origin of activation with clinically relevant accuracy.
Collapse
Affiliation(s)
- Peter Oosterhoff
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.).
| | - Veronique M F Meijborg
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Peter M van Dam
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Pascal F H M van Dessel
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Charly N W Belterman
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Geert J Streekstra
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Jacques M T de Bakker
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Ruben Coronel
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| | - Thom F Oostendorp
- From the Donders Institute for Brain, Cognition & Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands (P.O., P.M.v.D., T.F.O.); Department of Clinical and Experimental Cardiology (P.O., V.M.F.M., P.F.H.M.v.D., C.N.W.B., J.M.T.d.B., R.C.), and Department of Biomedical Engineering and Physics (G.J.S.), Academic Medical Center, Amsterdam, The Netherlands; ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (V.M.F.M., J.M.T.d.B.); and IHU Institut de Rythmologie et Modélisation Cardiaque, Fondation Bordeaux Université, Bordeaux, Pessac, France (R.C.)
| |
Collapse
|
39
|
Yang F, Zhang L, Lu W, Zhang Y, Zuo W, Wang K, Zhang H. A composite visualization method for electrophysiology-morphous merging of human heart. Biomed Eng Online 2017; 16:70. [PMID: 28595607 PMCID: PMC5465514 DOI: 10.1186/s12938-017-0368-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 06/01/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Electrophysiological behavior is of great importance for analyzing the cardiac functional mechanism under cardiac physiological and pathological condition. Due to the complexity of cardiac structure and biophysiological function, visualization of a cardiac electrophysiological model compositively is still a challenge. The lack of either modality of the whole organ structure or cardiac electrophysiological behaviors makes analysis of the intricate mechanisms of cardiac dynamic function a difficult task. This study aims at exploring 3D conduction of stimulus and electrical excitation reactivity on the level of organ with the authentic fine cardiac anatomy structure. METHODS In this paper, a cardiac electrical excitation propagation model is established based on the human cardiac cross-sectional data to explore detailed cardiac electrical activities. A novel biophysical merging visualization method is then presented for biophysical integration of cardiac anatomy and electrophysiological properties in the form of the merging optical model, which provides the corresponding position, spatial relationship and the whole process in 3D space with the context of anatomical structure for representing the biophysical detailed electrophysiological activity. RESULTS The visualization result present the action potential propagation of the left ventricle within the excitation cycle with the authentic fine cardiac organ anatomy. In the visualized images, all vital organs are identified and distinguished without ambiguity. The three dimensional spatial position, relation and the process of cardiac excitation conduction and re-entry propagation in the anatomical structure during the phase of depolarization and repolarization is also shown in the result images, which exhibits the performance of a more detailed biophysical understanding of the electrophysiological kinetics of human heart in vivo. CONCLUSIONS Results suggest that the proposed merging optical model can merge cardiac electrophysiological activity with the anatomy structure. By specifying the respective opacity for the cardiac anatomy structure and the electrophysiological model in the merging attenuation function, the visualized images can provide an in-depth insight into the biophysical detailed cardiac functioning phenomena and the corresponding electrophysiological behavior mechanism, which is helpful for further speculating cardiac physiological and pathological responses and is fundamental to the cardiac research and clinical diagnoses.
Collapse
Affiliation(s)
- Fei Yang
- School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, China
| | - Lei Zhang
- School of Art and Design, Harbin University, Harbin, China
| | - Weigang Lu
- Department of Educational Technology, Ocean University of China, Qingdao, China.
| | - Yue Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Wangmeng Zuo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Kuanquan Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Henggui Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.,School of Physics and Astronomy, University of Manchester, Manchester, M139PL, UK
| |
Collapse
|
40
|
Sánchez C, Bueno-Orovio A, Pueyo E, Rodríguez B. Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics. Front Bioeng Biotechnol 2017; 5:29. [PMID: 28534025 PMCID: PMC5420585 DOI: 10.3389/fbioe.2017.00029] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 04/18/2017] [Indexed: 12/19/2022] Open
Abstract
Atrial fibrillation (AF) usually manifests as reentrant circuits propagating through the whole atria creating chaotic activation patterns. Little is yet known about how differences in electrophysiological and ionic properties between patients modulate reentrant patterns in AF. The goal of this study is to quantify how variability in action potential duration (APD) at different stages of repolarization determines AF dynamics and their modulation by ionic block using a set of virtual whole-atria human models. Six human whole-atria models are constructed based on the same anatomical structure and fiber orientation, but with different electrophysiological phenotypes. Membrane kinetics for each whole-atria model are selected with distinct APD characteristics at 20, 50, and 90% repolarization, from an experimentally calibrated population of human atrial action potential models, including AF remodeling and acetylcholine parasympathetic effects. Our simulations show that in all whole-atria models, reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage, thus leading to higher dominant frequency (DF) and more organized activation in the left atrium than in the right atrium. Differences in APD in all phases of repolarization (not only APD90) yielded quantitative differences in fibrillation patterns with long APD associated with slower and more regular dynamics. Long APD50 and APD20 were associated with increased interatrial conduction block and interatrial differences in DF and organization index, creating reentry instability and self-termination in some cases. Specific inhibitions of IK1, INaK, or INa reduce DF and organization of the arrhythmia by enlarging wave meandering, reducing the number of secondary wavelets, and promoting interatrial block in all six virtual patients, especially for the phenotypes with short APD at 20, 50, and/or 90% repolarization. This suggests that therapies aiming at prolonging the early phase of repolarization might constitute effective antiarrhythmic strategies for the pharmacological management of AF. In summary, simulations report significant differences in atrial fibrillatory dynamics resulting from differences in APD at all phases of repolarization.
Collapse
Affiliation(s)
- Carlos Sánchez
- Biosignal Interpretation and Computational Simulation (BSICoS), I3A and IIS, University of Zaragoza, Zaragoza, Spain.,Defense University Centre (CUD), General Military Academy of Zaragoza (AGM), Zaragoza, Spain
| | | | - Esther Pueyo
- Biosignal Interpretation and Computational Simulation (BSICoS), I3A and IIS, University of Zaragoza, Zaragoza, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Blanca Rodríguez
- Department of Computer Science, University of Oxford, Oxford, UK
| |
Collapse
|
41
|
Lenis G, Pilia N, Loewe A, Schulze WHW, Dössel O. Comparison of Baseline Wander Removal Techniques considering the Preservation of ST Changes in the Ischemic ECG: A Simulation Study. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2017; 2017:9295029. [PMID: 28373893 PMCID: PMC5361052 DOI: 10.1155/2017/9295029] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 02/10/2017] [Accepted: 02/19/2017] [Indexed: 11/25/2022]
Abstract
The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered.
Collapse
Affiliation(s)
- Gustavo Lenis
- Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering (IBT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
| | - Nicolas Pilia
- Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering (IBT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
| | - Axel Loewe
- Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering (IBT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
| | | | - Olaf Dössel
- Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering (IBT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
| |
Collapse
|
42
|
Jacquemet V. Equivalent dipole sources to estimate the influence of extracellular myocardial anisotropy in thin-walled cardiac forward models. Math Biosci 2017; 286:31-38. [PMID: 28159543 DOI: 10.1016/j.mbs.2017.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 01/26/2017] [Accepted: 01/27/2017] [Indexed: 10/20/2022]
Abstract
The extracellular domain of the heart is anisotropic, which affects volume conduction and therefore body surface potentials. This paper tests the hypothesis that when wall thickness is sufficiently small (such as in the atria), the effect of extracellular anisotropy can be estimated by modifying local dipole current sources. A formula based on the Gabor-Nelson equivalent dipole and on the reciprocity theorem is derived to compute a linear transformation of the dipole sources that approximates in an isotropic volume conductor the far-field of the actual sources in an anisotropic volume conductor. It involves solving three Poisson equation (once for all). The results obtained in an atrial model embedded in a boundary-element torso model suggest that when wall thickness is < 3 mm, simulated P waves are weakly altered by extracellular anisotropy during sinus rhythm: an anisotropy ratio of 4:1 typically reduced the longitudinal component of the dipole sources by < 3%, increased the transverse component by < 5%, and increased the transmural component by ≈ 25% (which may be relevant in case of epicardial-endocardial dissociation). Due to uncertainty on experimental conductivity values, it is proposed that atrial extracellular anisotropy may be neglected when computing P waves.
Collapse
Affiliation(s)
- Vincent Jacquemet
- Université de Montréal, Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Montréal, Canada; Hôpital du Sacré-Coeur de Montréal, Centre de Recherche, 5400 boul. Gouin Ouest, Montréal, H4J 1C5, Canada.
| |
Collapse
|
43
|
Yang F, Zhang L, Lu W, Liu L, Zhang Y, Zuo W, Wang K, Zhang H. Depth Attenuation Degree Based Visualization for Cardiac Ischemic Electrophysiological Feature Exploration. BIOMED RESEARCH INTERNATIONAL 2016; 2016:2979081. [PMID: 28004002 PMCID: PMC5150122 DOI: 10.1155/2016/2979081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 09/21/2016] [Accepted: 10/11/2016] [Indexed: 01/23/2023]
Abstract
Although heart researches and acquirement of clinical and experimental data are progressively open to public use, cardiac biophysical functions are still not well understood. Due to the complex and fine structures of the heart, cardiac electrophysiological features of interest may be occluded when there is a necessity to demonstrate cardiac electrophysiological behaviors. To investigate cardiac abnormal electrophysiological features under the pathological condition, in this paper, we implement a human cardiac ischemic model and acquire the electrophysiological data of excitation propagation. A visualization framework is then proposed which integrates a novel depth weighted optic attenuation model into the pathological electrophysiological model. The hidden feature of interest in pathological tissue can be revealed from sophisticated overlapping biophysical information. Experiment results verify the effectiveness of the proposed method for intuitively exploring and inspecting cardiac electrophysiological activities, which is fundamental in analyzing and explaining biophysical mechanisms of cardiac functions for doctors and medical staff.
Collapse
Affiliation(s)
- Fei Yang
- School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264200, China
| | - Lei Zhang
- School of Art and Design, Harbin University, Harbin 150086, China
| | - Weigang Lu
- Department of Educational Technology, Ocean University of China, Qingdao 266100, China
| | - Lei Liu
- Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
| | - Yue Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Wangmeng Zuo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Kuanquan Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Henggui Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
- School of Physics and Astronomy, University of Manchester, Manchester M139PL, UK
| |
Collapse
|
44
|
Giffard-Roisin S, Jackson T, Fovargue L, Lee J, Delingette H, Razavi R, Ayache N, Sermesant M. Noninvasive Personalization of a Cardiac Electrophysiology Model From Body Surface Potential Mapping. IEEE Trans Biomed Eng 2016; 64:2206-2218. [PMID: 28113292 DOI: 10.1109/tbme.2016.2629849] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
GOAL We use noninvasive data (body surface potential mapping, BSPM) to personalize the main parameters of a cardiac electrophysiological (EP) model for predicting the response to different pacing conditions. METHODS First, an efficient forward model is proposed, coupling the Mitchell-Schaeffer transmembrane potential model with a current dipole formulation. Then, we estimate the main parameters of the cardiac model: activation onset location and tissue conductivity. A large patient-specific database of simulated BSPM is generated, from which specific features are extracted to train a machine learning algorithm. The activation onset location is computed from a Kernel Ridge Regression and a second regression calibrates the global ventricular conductivity. RESULTS The evaluation of the results is done both on a benchmark dataset of a patient with premature ventricular contraction (PVC) and on five nonischaemic implanted cardiac resynchonization therapy (CRT) patients with a total of 21 different pacing conditions. Good personalization results were found in terms of the activation onset location for the PVC (mean distance error, MDE = 20.3 mm), for the pacing sites (MDE = 21.7 mm) and for the CRT patients (MDE = 24.6 mm). We tested the predictive power of the personalized model for biventricular pacing and showed that we could predict the new electrical activity patterns with a good accuracy in terms of BSPM signals. CONCLUSION We have personalized the cardiac EP model and predicted new patient-specific pacing conditions. SIGNIFICANCE This is an encouraging first step towards a noninvasive preoperative prediction of the response to different pacing conditions to assist clinicians for CRT patient selection and therapy planning.
Collapse
|
45
|
Stenroos M. Integral equations and boundary-element solution for static potential in a general piece-wise homogeneous volume conductor. Phys Med Biol 2016; 61:N606-N617. [PMID: 27779140 DOI: 10.1088/0031-9155/61/22/n606] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Boundary element methods (BEM) are used for forward computation of bioelectromagnetic fields in multi-compartment volume conductor models. Most BEM approaches assume that each compartment is in contact with at most one external compartment. In this work, I present a general surface integral equation and BEM discretization that remove this limitation and allow BEM modeling of general piecewise-homogeneous medium. The new integral equation allows positioning of field points at junctioned boundary of more than two compartments, enabling the use of linear collocation BEM in such a complex geometry. A modular BEM implementation is presented for linear collocation and Galerkin approaches, starting from the standard formulation. The approach and resulting solver are verified in four ways, including comparisons of volume and surface potentials to those obtained using the finite element method (FEM), and the effect of a hole in skull on electroencephalographic scalp potentials is demonstrated.
Collapse
Affiliation(s)
- Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University, PO Box 12200, FI-00076 Aalto, Finland
| |
Collapse
|
46
|
ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone. Med Biol Eng Comput 2016; 55:979-990. [PMID: 27651061 DOI: 10.1007/s11517-016-1566-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 09/02/2016] [Indexed: 10/21/2022]
Abstract
ECG imaging is an emerging technology for the reconstruction of cardiac electric activity from non-invasively measured body surface potential maps. In this case report, we present the first evaluation of transmurally imaged activation times against endocardially reconstructed isochrones for a case of sustained monomorphic ventricular tachycardia (VT). Computer models of the thorax and whole heart were produced from MR images. A recently published approach was applied to facilitate electrode localization in the catheter laboratory, which allows for the acquisition of body surface potential maps while performing non-contact mapping for the reconstruction of local activation times. ECG imaging was then realized using Tikhonov regularization with spatio-temporal smoothing as proposed by Huiskamp and Greensite and further with the spline-based approach by Erem et al. Activation times were computed from transmurally reconstructed transmembrane voltages. The results showed good qualitative agreement between the non-invasively and invasively reconstructed activation times. Also, low amplitudes in the imaged transmembrane voltages were found to correlate with volumes of scar and grey zone in delayed gadolinium enhancement cardiac MR. The study underlines the ability of ECG imaging to produce activation times of ventricular electric activity-and to represent effects of scar tissue in the imaged transmembrane voltages.
Collapse
|
47
|
Bomzon Z, Urman N, Wenger C, Giladi M, Weinberg U, Wasserman Y, Kirson ED, Miranda PC, Palti Y. Modelling Tumor Treating Fields for the treatment of lung-based tumors. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2015:6888-91. [PMID: 26737876 DOI: 10.1109/embc.2015.7319976] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Tumor Treating Fields (TTFields), low-intensity electric fields in the frequency range of 100-500 kHz, exhibit antimitotic activity in cancer cells. TTFields were approved by the U. S. Food and Drug Administration for the treatment of recurrent glioblastoma in 2011. Preclinical evidence and pilot studies suggest that TTFields could be effective for treating certain types of lung cancer, and that treatment efficacy depends on the electric field intensity. To optimize TTFields delivery to the lungs, it is important to understand how TTFields distribute within the chest. Here we present simulations showing how TTFields are distributed in the thorax and torso, and demonstrate how the electric field distribution within the body can be controlled by personalizing the layout of the arrays used to deliver the field.
Collapse
|
48
|
Voloshin T, Munster M, Blatt R, Shteingauz A, Roberts PC, Schmelz EM, Giladi M, Schneiderman RS, Zeevi E, Porat Y, Bomzon Z, Urman N, Itzhaki A, Cahal S, Kirson ED, Weinberg U, Palti Y. Alternating electric fields (TTFields) in combination with paclitaxel are therapeutically effective against ovarian cancer cells in vitro and in vivo. Int J Cancer 2016; 139:2850-2858. [PMID: 27561100 PMCID: PMC5095795 DOI: 10.1002/ijc.30406] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Accepted: 08/15/2016] [Indexed: 11/07/2022]
Abstract
Long-term survival rates for advanced ovarian cancer patients have not changed appreciably over the past four decades; therefore, development of new, effective treatment modalities remains a high priority. Tumor Treating Fields (TTFields), a clinically active anticancer modality utilize low-intensity, intermediate frequency, alternating electric fields. The goal of this study was to evaluate the efficacy of combining TTFields with paclitaxel against ovarian cancer cells in vitro and in vivo. In vitro application of TTFields on human ovarian cancer cell lines led to a significant reduction in cell counts as compared to untreated cells. The effect was found to be frequency and intensity dependent. Further reduction in the number of viable cells was achieved when TTFields treatment was combined with paclitaxel. The in vivo effect of the combined treatment was tested in mice orthotopically implanted with MOSE-LTICv cells. In this model, combined treatment led to a significant reduction in tumor luminescence and in tumor weight as compared to untreated mice. The feasibility of effective local delivery of TTFields to the human abdomen was examined using finite element mesh simulations performed using the Sim4life software. These simulations demonstrated that electric fields intensities inside and in the vicinity of the ovaries of a realistic human computational phantom are about 1 and 2 V/cm pk-pk, respectively, which is within the range of intensities required for TTFields effect. These results suggest that prospective clinical investigation of the combination of TTFields and paclitaxel is warranted.
Collapse
Affiliation(s)
- Tali Voloshin
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Mijal Munster
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Roni Blatt
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Anna Shteingauz
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Paul C Roberts
- Department of Biomedical Sciences and Pathobiology and Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA, 24061
| | - Eva M Schmelz
- Department of Biomedical Sciences and Pathobiology and Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA, 24061
| | - Moshe Giladi
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel.
| | | | - Einav Zeevi
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Yaara Porat
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Ze'ev Bomzon
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Noa Urman
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Aviran Itzhaki
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Shay Cahal
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Eilon D Kirson
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Uri Weinberg
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| | - Yoram Palti
- Novocure Ltd. Topaz Building, MATAM center, Haifa, 31905, Israel
| |
Collapse
|
49
|
Image Segmentation for Cardiovascular Biomedical Applications at Different Scales. COMPUTATION 2016. [DOI: 10.3390/computation4030035] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
50
|
Kolomeyets NL, Roshchevskaya IM. The electrical resistivity of a segment of the tail, lungs, liver, and intercostal muscles of the grass snake during in vivo cooling. Biophysics (Nagoya-shi) 2016. [DOI: 10.1134/s0006350916050110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
|